CLASSIFICATION ENVIRONMENTAL SOUND WITH WAVELET

Abstract

Sound signals can deliver important information about the environment. Therefore, recognition and assessment of these signals are very useful for surveillance purposes. Reaching new methods that have highest accuracy and lowest calculating time is ideal. Generally, wavelet method is used in environmental sound classification. In this paper, we propose both continuous and discrete wavelet transform. Firstly, three features are extracted from signal through calculating its scalogram, and secondly, we decompose signals with daubechies mother wavelet in 4 level and calculate B-spline coefficient and then extract three features from them. Finally, we evaluate this method on 80 sound segment from two airplane collected from a public database. It takes 1.3s for calculating the 0.2 seconds of sound segment. In the end combining these methods help reach a higher accuracy percentage compared to the previous works.